The concept of core collections as developed by Brown (1989a) would be very useful in optimizing conservation strategies of natural population of outbreeding grasses. The aim of a core is to represent, in a subsample of manageable size, as much as possible of the genetic variation from a large collection. In the case of natural populations of ryegrass, different methods of stratified sampling with one level of classification have been compared:
Clustering based on agronomic traits.
Clustering based on the administrative region of origin.
Clustering based on agronomic traits with geographic contiguity constraint.
This last method is based on geostatistics analysis, which allows to study the spatial pattern of genetic diversity. Ryegrass populations show for many agronomic traits a spatial structure of range 120 km, which could be attributed to the isolation-by-distance phenomenon. This range was used as a constraint for clustering populations based on multisite evaluation data.
The results show that, in a species like perennial ryegrass, a random sample of 5% of the accessions maintains 86% of the diversity. Core samples of 10% as recommended by Brown (1989b) enhance the representation to more than 90%. The use of stratified sampling methods is always more efficient than random sampling. The clustering based on geostatistics gives the best results with 92% of the variation being maintained in a 5% core collection.
genetic resourcescore collectionsamplingLolium perenne L